{"title":"在学习神经网络波函数的同时教授自旋对称。","authors":"Yongle Li, Yuhao Chen, Xiao He","doi":"10.1038/s43588-024-00727-z","DOIUrl":null,"url":null,"abstract":"By developing an efficient spin symmetry penalty, a recent study has substantially accelerated the calculation of accurate energies with correct spin states in variational Monte Carlo for both ground and excited states of quantum many-particle systems.","PeriodicalId":74246,"journal":{"name":"Nature computational science","volume":"4 12","pages":"884-885"},"PeriodicalIF":12.0000,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Teaching spin symmetry while learning neural network wave functions\",\"authors\":\"Yongle Li, Yuhao Chen, Xiao He\",\"doi\":\"10.1038/s43588-024-00727-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"By developing an efficient spin symmetry penalty, a recent study has substantially accelerated the calculation of accurate energies with correct spin states in variational Monte Carlo for both ground and excited states of quantum many-particle systems.\",\"PeriodicalId\":74246,\"journal\":{\"name\":\"Nature computational science\",\"volume\":\"4 12\",\"pages\":\"884-885\"},\"PeriodicalIF\":12.0000,\"publicationDate\":\"2024-12-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nature computational science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.nature.com/articles/s43588-024-00727-z\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature computational science","FirstCategoryId":"1085","ListUrlMain":"https://www.nature.com/articles/s43588-024-00727-z","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Teaching spin symmetry while learning neural network wave functions
By developing an efficient spin symmetry penalty, a recent study has substantially accelerated the calculation of accurate energies with correct spin states in variational Monte Carlo for both ground and excited states of quantum many-particle systems.
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